Efficient Verification of a RADAR SoC Using Formal and Simulation-Based Methods

Abstract--As the demand for Internet of Things (IoT) and Human-to-Machine Interaction (HMI) increases, modern System-on-Chips (SoCs) offering such solutions are becoming increasingly complex. This intricate design poses significant challenges for verification, particularly when time-to-market is a crucial factor for consumer electronics products. This paper presents a case study based on our work to verify a complex Radio Detection And Ranging (RADAR) based SoC that performs on-chip sensing of human motion with millimetre accuracy [1]. We leverage both formal and simulation-based methods to complement each other and achieve verification sign-off with high confidence [2]. While employing a requirements-driven flow approach [3], we demonstrate the use of different verification methods to cater to multiple requirements and highlight our know-how from the project. Additionally, we used Machine Learning (ML) based methods, specifically the Xcelium ML tool from Cadence, to improve verification throughput [4]. Verification has become the bottleneck in product development cycles, as it takes more than 60 % of the overall project time [5]. Complex designs such as RADAR-based SoC contribute even more to the challenges in verification on top of existing ones.